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Clickbait Detection Using Swarm Intelligence

  • Deepanshu Pandey
  • Garimendra VermaEmail author
  • Sushama Nagpal
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 968)

Abstract

Clickbaits are the articles containing catchy headlines which lure the reader to explore full content, but do not have any useful information. Detecting clickbaits solely by the headline without opening the link, can serve as a utility for users over internet. This can prevent their time from useless surfing caused by exploring clickbaits. In this paper Ant Colony Optimization, a Swarm Intelligence (SI) based technique has been used to detect clickbaits. In comparison with algorithms used in the past, this SI based technique provided a better accuracy and a human interpretable set of rules to classify clickbaits. A maximum accuracy of 96.93% with a set of 20 classification rules was obtained using the algorithm.

Keywords

Clickbaits Ant Colony Optimization (ACO) Classification 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Deepanshu Pandey
    • 1
  • Garimendra Verma
    • 1
    Email author
  • Sushama Nagpal
    • 1
  1. 1.Netaji Subhas Institute of TechnologyDelhiIndia

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